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TISCOPE enables integrative and comparative analyses of spatial omics data to reveal condition-associated tissue modules

TISCOPE

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Installation

  1. We recommend creating a virtual environment using Python 3.11:
conda create -n tiscope python=3.11
conda activate tiscope
  1. (Skip if PyTorch is already installed) install PyTorch following the PyTorch installation guide. For example, on a machine with cuda 12.x:
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu126
  1. (Skip if PyG is already installed) Install PyG following the PyG installation guide, usually:
pip install torch_geometric
  1. Install dependencies:
pip install 'scanpy[leiden]' louvain squidpy ipykernel
  1. Install TISCOPE:

Via Pypi:

pip install tiscope

or git clone and install

git clone git://github.com/zhangqf-lab/TISCOPE.git
cd tiscope
pip install -e .

Getting started

Please refer to the Documentation.

Release notes

Citation

Release files for tiscope 0.0.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for tiscope 0.0.2
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tiscope-0.0.2.tar.gz 16.3 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for tiscope 0.0.2
File Interpreter ABI Platform
tiscope-0.0.2-py3-none-any.whl Python 3 none any Details

Total release size: 33.2 kB

Release files / tiscope-0.0.2.tar.gz

Download URL tiscope-0.0.2.tar.gz
Size 16.3 kB
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Release files / tiscope-0.0.2-py3-none-any.whl

Download URL tiscope-0.0.2-py3-none-any.whl
Size 16.8 kB
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Uploaded via twine/6.2.0 CPython/3.9.6

Release history Release notifications | RSS feed

This release

0.0.2 This release

2 release files

0.0.1

2 release files

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